wehub-resource-sync
67 lines
2.1 KiB
Java
67 lines
2.1 KiB
Java
package org.opencv.test.dnn;
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import java.util.ArrayList;
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import java.util.List;
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import org.opencv.core.Core;
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import org.opencv.core.CvType;
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import org.opencv.core.Mat;
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import org.opencv.core.MatOfByte;
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import org.opencv.core.Range;
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import org.opencv.dnn.Dnn;
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import org.opencv.dnn.Net;
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import org.opencv.test.OpenCVTestCase;
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public class DnnForwardAndRetrieve extends OpenCVTestCase {
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public void testForwardAndRetrieve()
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{
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// Create a simple Caffe prototxt with a Slice layer
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String prototxt =
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"input: \"data\"\n" +
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"layer {\n" +
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" name: \"testLayer\"\n" +
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" type: \"Slice\"\n" +
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" bottom: \"data\"\n" +
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" top: \"firstCopy\"\n" +
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" top: \"secondCopy\"\n" +
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" slice_param {\n" +
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" axis: 0\n" +
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" slice_point: 2\n" +
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" }\n" +
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"}";
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// Read network from prototxt
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MatOfByte bufferProto = new MatOfByte();
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bufferProto.fromArray(prototxt.getBytes());
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Net net = Dnn.readNetFromCaffe(bufferProto);
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net.setPreferableBackend(Dnn.DNN_BACKEND_OPENCV);
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// Create input data
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Mat inp = new Mat(4, 5, CvType.CV_32F);
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Core.randu(inp, -1, 1);
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net.setInput(inp);
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// Define output names
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List<String> outNames = new ArrayList<>();
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outNames.add("testLayer");
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// Forward and retrieve multiple outputs
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List<List<Mat>> outBlobs = new ArrayList<>();
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net.forwardAndRetrieve(outBlobs, outNames);
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// Verify results
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assertEquals(1, outBlobs.size());
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assertEquals(2, outBlobs.get(0).size());
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// Compare results
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Mat expectedFirst = inp.rowRange(0, 2);
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Mat expectedSecond = inp.rowRange(2, 4);
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Mat actualFirst = outBlobs.get(0).get(0);
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Mat actualSecond = outBlobs.get(0).get(1);
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assertEquals(0, Core.norm(expectedFirst, actualFirst, Core.NORM_INF), EPS);
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assertEquals(0, Core.norm(expectedSecond, actualSecond, Core.NORM_INF), EPS);
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}
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}
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